A Two-Step Iterative Algorithm For Estimation In Nonlinear Mixed-Effect Models With An Evaluation In Population Pharmacokinetics

DOI10.1080/10543409508835104zbMath0907.62128OpenAlexW2039534486WikidataQ52337597 ScholiaQ52337597MaRDI QIDQ4216073

France Mentré, Roberto Gomeni

Publication date: 4 March 1999

Published in: Journal of Biopharmaceutical Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10543409508835104

zbMATH Keywords

EM algorithmpharmacokineticspharmacodynamic modelingcovariate handlingnonlinear random-effect modelpopulation parameter estimation

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Kinetics in biochemical problems (pharmacokinetics, enzyme kinetics, etc.) (92C45)

Related Items (2)

Convergence rate of MLE in generalized linear and nonlinear mixed-effects models: Theory and applications ⋮ Strong consistency of the maximum likelihood estimator in generalized linear and nonlinear mixed-effects models

Cites Work

• Random-Effects Models for Longitudinal Data
• Empirical Bayes Estimation of Individual Growth-Curve Parameters and Their Relationship to Covariates
• Maximum likelihood estimation via the ECM algorithm: A general framework
• Hyperparameter Estimation Using Stochastic Approximation with Application to Population Pharmacokinetics
• A Bayesian Approach to Nonlinear Random Effects Models
• Newton-Raphson and EM Algorithms for Linear Mixed-Effects Models for Repeated-Measures Data
• An Algorithm for Least-Squares Estimation of Nonlinear Parameters
• Bayesian Analysis of Linear and Non-Linear Population Models by Using the Gibbs Sampler

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